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GLM 5.3 FlashX vs GPT-3.5 Turbo (older v0613)

GLM 5.3 FlashX costs 1.6x less per output token than GPT-3.5 Turbo (older v0613) ($1.25 vs $2.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace GLM 5.3 FlashX Replace GPT-3.5 Turbo (older v0613)
GLM 5.3 FlashXZ.ai
Coding
No data
Overall
No data
Output $/M
$1.25
GPT-3.5 Turbo (older v0613)OpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
vs $1.25 vs $2.00 per 1M output tokens. GLM 5.3 FlashX is 1.6x cheaper.

GLM 5.3 FlashX or GPT-3.5 Turbo (older v0613): which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GLM 5.3 FlashX for output tokens 1.6x cheaper ($1.25 vs $2.00 per million) and a larger context window (1.05M against 4K tokens).

Model AGLM 5.3 FlashXZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-3.5 Turbo (older v0613)OpenAINot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. GLM 5.3 FlashX has none yet; GPT-3.5 Turbo (older v0613) on GSM8K, MMLU and WinoGrande. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GLM 5.3 FlashX not benchmarked, GPT-3.5 Turbo (older v0613) not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
GLM 5.3 FlashX $1.25 against GPT-3.5 Turbo (older v0613) $2.00 per million output tokens, 1.6x apart.
Context window
GLM 5.3 FlashX takes 1.05M tokens, GPT-3.5 Turbo (older v0613) 4K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Math benchmarks for GLM 5.3 FlashX and GPT-3.5 Turbo (older v0613)
BenchmarkGLM 5.3 FlashXGPT-3.5 Turbo (older v0613)Leader
GSM8KNot measured46.9%Only GPT-3.5 Turbo (older v0613) measured
Neither model has a result on the other 13 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Knowledge benchmarks for GLM 5.3 FlashX and GPT-3.5 Turbo (older v0613)
BenchmarkGLM 5.3 FlashXGPT-3.5 Turbo (older v0613)Leader
MMLUNot measured68.9%Only GPT-3.5 Turbo (older v0613) measured
Neither model has a result on the other 19 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
General benchmarks for GLM 5.3 FlashX and GPT-3.5 Turbo (older v0613)
BenchmarkGLM 5.3 FlashXGPT-3.5 Turbo (older v0613)Leader
WinoGrandeNot measured81.6%Only GPT-3.5 Turbo (older v0613) measured
Neither model has a result on the other 47 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GLM 5.3 FlashX$0.0010Fits in one request
GPT-3.5 Turbo (older v0613)$0.0020Fits in one request

GLM 5.3 FlashX costs less

Repository review

50K input + 3K output tokens

GLM 5.3 FlashX$0.022Fits in one request
GPT-3.5 Turbo (older v0613)$0.056Exceeds the context window

GLM 5.3 FlashX costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 FlashX$0.086Fits in one request
GPT-3.5 Turbo (older v0613)$0.220Exceeds the context window

GLM 5.3 FlashX costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GLM 5.3 FlashX and GPT-3.5 Turbo (older v0613)
SpecificationZ.ai GLM 5.3 FlashXOpenAI GPT-3.5 Turbo (older v0613)
MakerZ.aiOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 18, 2026January 25, 2024
Context window1.05M4K
Input $/Mtok$0.37$1.00
Output $/Mtok$1.25$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 FlashX better than GPT-3.5 Turbo (older v0613) for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5.3 FlashX for output tokens 1.6x cheaper ($1.25 vs $2.00 per million) and a larger context window (1.05M against 4K tokens).

Which is cheaper, GLM 5.3 FlashX or GPT-3.5 Turbo (older v0613)?

GLM 5.3 FlashX costs $0.37 per million input tokens and $1.25 per million output tokens; GPT-3.5 Turbo (older v0613) costs $1.00 and $2.00. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 5.3 FlashX or GPT-3.5 Turbo (older v0613)?

GLM 5.3 FlashX, with 1.05M tokens against 4K.

Has any benchmark tested both GLM 5.3 FlashX and GPT-3.5 Turbo (older v0613)?

No benchmark has tested both yet. GLM 5.3 FlashX has none yet; GPT-3.5 Turbo (older v0613) on GSM8K, MMLU and WinoGrande. Compare them on price and context instead. Data as of October 22, 2026.

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